Predictive analysis of seismic damage to buildings near-surface faults under the influence of multiple factors

Jianyi Zhang, Zishan Bai, Jianke Ma, Shihang Qu, Jing Tian, Shuai Wang and Ran Zhang

PLOS ONE, 2025, vol. 20, issue 5, 1-17

Abstract: The investigation and analysis of building damage is the most direct and effective method to reveal its mechanism, but the statistics and analysis of building damage sample data near surface faults are obviously insufficient. Therefore, based on the influencing factors of building damage near surface faults, this article predicts the structural damage caused by the surface rupture effect of active faults. Through on-site investigation of earthquake damage and literature review, data collection was conducted on the seismic damage characteristics of buildings near surface fault zones, and a database of building damage near strong earthquake surface fault zones was established. Multiple linear and binary logistic regression models were used to quantitatively analyze the seismic damage of buildings. The results indicate that magnitude, types of fault, hanging wall and footwall of faults, width of surface rupture zone, fault distance, and vertical displacement have a significant impact on the seismic damage index of buildings. Based on earthquake damage examples, both prediction models have significant performance.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0320930

DOI: 10.1371/journal.pone.0320930

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